Evaluation of Innovative Design of Clothing Image Elements Using Image Processing

Abstract

Excellent design of clothing image elements can enhance the attractiveness of clothing to customers. This paper used image processing technology to extract texture and color features for innovative designs of clothing image elements and used the convolutional neural network (CNN) model to evaluate some designs. The CNN model was compared with the back-propagation neural network (BPNN) model in the example analysis, and three designs were evaluated. The results showed that the image processing-based CNN model had good evaluation performance and obtained evaluation results closer to the manual evaluation results than the BPNN model. The evaluation results of the three designs also showed that all three designs achieved innovative design through effectively combining multiple image elements.